A four point algorithm for fast metric cone reconstruction from a calibrated image

Jin Zhou, Baoxin Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a four point algorithm for fast metric reconstruction of a cone from a single calibrated image. The algorithm first estimates the camera's orientation based on two edge lines and a cross section contour, which are derived from user-specified four points. With camera's orientation determined, the cone is reconstructed from the image points. The algorithm enables fast and accurate modeling of cone objects from images, which is verified by the experiments.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages634-643
Number of pages10
Volume5359 LNCS
EditionPART 2
DOIs
StatePublished - 2008
Event4th International Symposium on Visual Computing, ISVC 2008 - Las Vegas, NV, United States
Duration: Dec 1 2008Dec 3 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5359 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Symposium on Visual Computing, ISVC 2008
CountryUnited States
CityLas Vegas, NV
Period12/1/0812/3/08

Fingerprint

Cones
Cone
Metric
Camera
Cameras
Fast Algorithm
Cross section
Line
Modeling
Estimate
Experiment
Experiments
Object

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Zhou, J., & Li, B. (2008). A four point algorithm for fast metric cone reconstruction from a calibrated image. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 5359 LNCS, pp. 634-643). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5359 LNCS, No. PART 2). https://doi.org/10.1007/978-3-540-89646-3_62

A four point algorithm for fast metric cone reconstruction from a calibrated image. / Zhou, Jin; Li, Baoxin.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5359 LNCS PART 2. ed. 2008. p. 634-643 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5359 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhou, J & Li, B 2008, A four point algorithm for fast metric cone reconstruction from a calibrated image. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 edn, vol. 5359 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5359 LNCS, pp. 634-643, 4th International Symposium on Visual Computing, ISVC 2008, Las Vegas, NV, United States, 12/1/08. https://doi.org/10.1007/978-3-540-89646-3_62
Zhou J, Li B. A four point algorithm for fast metric cone reconstruction from a calibrated image. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 ed. Vol. 5359 LNCS. 2008. p. 634-643. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-540-89646-3_62
Zhou, Jin ; Li, Baoxin. / A four point algorithm for fast metric cone reconstruction from a calibrated image. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5359 LNCS PART 2. ed. 2008. pp. 634-643 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).
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